During flights with recommendations, fairly frequent naps were taken. Naps lasted between 20 minutes and 90 minutes and significantly reduced the number of alertness decrements.
This leads to a global reduction in the alertness decrement rates, especially during cruise phases. We can also see that these naps have a beneficial effect on the alertness level during descent.
The syeses included in this brochure are the same as those is
Rather the intention here is simply to summarize their development and to give some idea as to how they operate. Interested readers are referred to a meeting that was held in Seattle in June 2002 at which seven of the models were presented and evaluated. The edited proceedings of this meeting will shortly (2003) be published as a special supplement to the journal “Aviation Space and Environmental Medicine”. (see http://fatigue.anteon.com/announce.htm for further details).
Most of th
from individuals on abnormal sleep/wake schedules. They rely on the fact that under these conditions it is sometimes possible to make separate estimates of the endogenous and exogenous (or homeostatic) components of alertness or fatigue. The former component reflects on the influence of the “body clock” while the latter These two models showed a substantial agreeme
the body clock component of alertness to be sinusoidal in nature, with a peak at about 17:00, and the homeostatic component to result in a decrease over most of the time spent awake. The only exception to this monotonic decrease in alertness over time awake due to the homeostatic component occurred during the first two to three hours after awakening when alertness was rather lower than might be expected. This was thought to reflect on a “wake up” or “sleep inertia” effect and was modeled by Folkard and .kerstedt (1987) as a short-lived exponential decrease in alertness. The two main components of the Folkard and .kerstedt (1987) model are illustrated in the following figure. This shows the overall trend in alertness for someone taking a “day-sleep” between two successive night duties, Note that alertness is modeled as decreasing exponentially over time awake and recovering exponentially during sleep. The overall trend in alertness is simply the sum of the underlying components. As shown in the following figure, the overall trend in alertness for someone on a night duty (green line) together w
homeostatic (red line) components of this trend. 15
increased our understanding in this area and have resulted in a number of more applied versions aimed at, for example, predicting the fatigue levels of long-haul pilots. However, as one of the organizers of the Seattle meeting concluded, the predictions from the various models agree with one another rather better than they do with the raw data! Further, it is notable that the models cannot currently account for the well-established trends in the risk of accidents and injuries associated with various features of shift systems (Folkard & .kerstedt 2003). Thus, although the development of models has increased our knowledge in this important field, we are still some way from being able to use them with any certainty in applied situations.
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